CHARACTERIZING SYMPTOM BURDEN AMONG COMMUNITY-DWELLING OLDER ADULTS

Abstract One-third of symptoms reported by older adults are unexplained and not directly related to a chronic disease diagnosis. This ambiguity contributes to undertreatment and chronic functional burdens in vulnerable older patients. Previous studies have found that older adults often experience multiple co-occurring symptoms that contribute to disablement. Symptom burden in older adults increases healthcare utilization, decrease physical performance, and leads to poorer quality of life. This study aimed to characterize symptom burden in a population-based cohort of community-dwelling older adults enrolled in the MOBILIZE Boston study (n=765). We used descriptive statistics for symptom prevalence including pain, balance, weakness, endurance, sleep difficulty, depression/anxiety and sensory impairments. We used latent class analysis to identify 4 distinct classes based on overall symptom burden: 1) mild (26.6%), 2) moderate (53.8%), 3) moderate-severe (12%) and 4) severe (7.5%). Moderate to high levels of pain, the most prevalent symptom, were reported in all symptom burden classes except the mild class. Older adults with severe symptom burden, group 4, experienced worse levels of all symptoms compared to other classes. They also experienced moderate endurance and weakness symptoms, and mild and/or severe balance symptoms. Older adults in the moderate-severe class tended to also report mild endurance, balance, and weakness symptoms. Understanding overall symptom burden, both in terms of numbers and severity of symptoms, is the first step in determining the impact of symptom burden as a possible new clinical indicator for fall risk and other detrimental health outcomes.

sample: mean CCI increased from 1.69 to 1.97 and mean ECI increased from 3.66 to 4.14.Comorbidity scores were higher over time with increasing age until about age 80-84 (for CCI) and age 85-89 (for ECI) and increased similarly among males and females.Black and Native American inpatients had the largest increase in mean CCI and ECI scores.Comorbidities with increased hospitalization rates included congestive heart failure (+5%), dementia (+6%), complicated diabetes (+14%), complicated hypertension (+17%), renal disease/failure (+5%), and obesity (+5%).Growing disease burden among inpatients supports the continued need for programs aiming to prevent and treat chronic diseases and multimorbidity, especially among underrepresented populations including Black and Native American communities.The COVID-19 pandemic drastically changed how nursing homes facilitated visitation between residents and their families.Nursing homes needed to modify visitation approaches in response to changing policies and guidelines from varying governing bodies.Additionally, restrictions were constantly adjusted due to fluctuations in COVID-19 infection rates within facilities and the larger communities in which they exist.Through data from 156 in-depth, semi-structured interviews with nursing home administrators, conducted at three-month intervals throughout the COVID-19 pandemic, administrator experiences are captured as they navigated these changes.Interviews provide valuable insight into strategies used during shut-down of in-person visitation, allowance of compassionate care and essential caregiver visits, and the resumption of in-person visitation, while also demonstrating the challenges of each visitation stage and the second-hand emotional responses of resident families.During the shut-down of in-person visitation, facilities conducted virtual visits and implemented new strategies including parades and window visits.Compassionate care and essential caregiver visits were used for those in hospice or experiencing weight loss and depression resulting from restrictions, though some administrators reported being flexible in their definitions of compassionate and essential caregiver visits.When in-person visitation resumed, interviews highlight the use of screening, social distancing, and monitoring during indoor visitation, as well as the approaches facilities took to respond to the challenges of staffing shortages and outbreak concerns.Study findings provide insight into how facilities may navigate future visitation changes and restrictions to maximize safety, the overall well-being of residents and the efficiency of facilitating visits.
One-third of symptoms reported by older adults are unexplained and not directly related to a chronic disease diagnosis.This ambiguity contributes to undertreatment and chronic functional burdens in vulnerable older patients.Previous studies have found that older adults often experience multiple co-occurring symptoms that contribute to disablement.Symptom burden in older adults increases healthcare utilization, decrease physical performance, and leads to poorer quality of life.This study aimed to characterize symptom burden in a population-based cohort of community-dwelling older adults enrolled in the MOBILIZE Boston study (n=765).We used descriptive statistics for symptom prevalence including pain, balance, weakness, endurance, sleep difficulty, depression/anxiety and sensory impairments.We used latent class analysis to identify 4 distinct classes based on overall symptom burden: 1) mild (26.6%), 2) moderate (53.8%), 3) moderate-severe (12%) and 4) severe (7.5%).Moderate to high levels of pain, the most prevalent symptom, were reported in all symptom burden classes except the mild class.Older adults with severe symptom burden, group 4, experienced worse levels of all symptoms compared to other classes.They also experienced moderate endurance and weakness symptoms, and mild and/or severe balance symptoms.Older adults in the moderate-severe class tended to also report mild endurance, balance, and weakness symptoms.Understanding overall symptom burden, both in terms of numbers and severity of symptoms, is the first step in determining the impact of symptom burden as a possible new clinical indicator for fall risk and other detrimental health outcomes.

CHATGPT, WHAT IS A DEDUCTIBLE? DIGITAL ASSISTANTS AS AN INFORMATION SOURCE FOR MEDICARE QUERIES
Emily Langston, Neil Charness, and Walter Boot, Florida State University, Tallahassee, Florida, United States Since being first introduced to the public in late 2022, chatbots that are based on large language models (LLMs) have attracted a great deal of attention.However, despite their popularity, these chatbots have been shown to give inaccurate information in response to user queries.Several polls conducted in 2022 suggest that the public is generally skeptical about the use of Artificial Intelligence (AI), particularly in the context of healthcare, and older adults are the most distrustful age group, despite the fact that they are the least likely to have interacted with an LLM such as ChatGPT.Meta-analysis on trust in AI has shown that users are most influenced by the accuracy and reliability of the AI trustee.In our study, we assessed the accuracy of speaker-based assistants, Alexa and Google Assistant, as well as two LLMs, Bard and ChatGPT4 on Medicare terminology and knowledge and compared their accuracy to that of a large representative sample of Medicare beneficiaries.Google Assistant was found to perform significantly worse than beneficiaries on both terminology and knowledge questions.Alexa was found to perform significantly worse than beneficiaries on terminology questions.Conversely, both Bard and ChatGPT4 were found to perform significantly better than beneficiaries on both terminology and knowledge questions.We conclude that Medicare beneficiaries should not rely on Google Assistant for terminology help or general knowledge queries, nor should they rely on Alexa for terminology help.ChatGPT4 and Bard are potentially valuable resources for beneficiaries with terminology-based and general knowledge queries.

CHILDHOOD ADVERSITY IS ASSOCIATED WITH MENTAL HEALTH BUT NOT COGNITIVE DECLINE IN OLDER ADULTS
James Lian 1 , Kim Kiely 2 , Bridget Callaghan 3 , and Kaarin Anstey 1 , 1. University of New South Wales, Sydney, New South Wales, Australia, 2. University of Wollongong, Sydney, New South Wales, Australia, 3. University of California, Los Angeles, Los Angeles, California, United States Objective: The aim of this study was to examine the association between childhood adversity and mental health and cognition in older adults.Methods: The sample included older Australian adults from the Personality and Total Health (PATH) Through Life Project (N = 2551).Childhood adversity was measured using a 17-item scale of domestic adversities (e.g., poverty, neglect, physical abuse, verbal abuse) and modelled using cumulative risk analysis (LCA).Mental health was measured using four validated depression and anxiety questionnaires and cognitive impairment was determined by a clinically validated algorithmic diagnostic criteria.The association between childhood adversity and late-life mental health was estimated using generalised additive models, and the association with cognition utilised multiple logistic regressions.Models were adjusted for gender, race, and education.Results: Generalised additive models indicated that a greater number of cumulative adversities were associated with poorer scores on all four mental health measures.No notable interactions between ACEs and gender were observed.In contrast, there was no association between childhood adversity and cognitive impairment in any of the tested logistic regression models.No gender differences were observed and no interactions with education or genotype were found.Conclusion: Consistent with prevailing literature, our study provides additional evidence for the enduring effects of domestic childhood adversity on anxiety and depression in older adulthood.Furthermore, the absence of associations between early adversity and cognitive impairment indicates that other factors might play a more prominent role in determining late-life cognitive outcomes.

CHILDHOOD SOCIOECONOMIC STATUS GRADIENTS IN FUNCTIONAL LIMITATIONS: THE ROLE OF MACRO-ECONOMIC CONTEXT
Thomas Fuller-Rowell 1 , Samia Sultana 1 , Amy Hudson 1 , Eric Kim 2 , and Carol Ryff 3 , 1. Auburn University, Auburn,Alabama,United States,2. University of British Columbia,Vancouver,British Columbia,Canada,Madison,Wisconsin,United States A large number of studies have documented an association between childhood socioeconomic status (SES) and adult health or illness.However, relatively little is known about how this SES-health gradient varies across macroeconomic contexts.The current study examined state-level mean income as a moderator of the association between the education level of a person's parents and functional limitations in the United States (N = 10,685, Mean age = 47.7,